With product monopolies disappearing very fast and competition ever increasing, today a consumer has scores of options in every aspect of life. One direct consequence of this competition is that the products are being aimed to suit more and more personalized needs of the consumer. On the other hand with explosion of cable TV and Internet, a consumer has become more accessible to the advertiser than ever before. Result of these two developments has generated current interest in targeted advertising which mainly aims at the effective use of the personal media for more result-oriented advertising. Third generation mobile phone shall play an important role in enhancing the effectiveness of target advertisement in near future. Unlike the previous strategies of targeted advertisement, where the targeting can be focused at a level of a community or geographical location, targeting can now be focused on an individual through their mobile phones or personal desktops. This improves the impact of the advertisement on the consumer and possibly increases the probability of purchase of the product. Technology related to third and fourth generation mobile telephony and its potential to provide rich audio visual content to the user has created a large number of new possibilities for target advertising.
The key to success of target advertising lies in the precision of selecting right advertisement for a potential buyer or right buyer for a given advertisement. Contrary to this, the normal advertisement on a conventional media aims at larger audience rather than greater precision. The importance of precision in target advertising comes from the fact that the cost of advertising is directly proportional to number of potential buyers addressed and therefore any miss-target means wastage of resources. However, targeting the right buyer has always been a difficult task. Some of the prior art focused on identifying target groups and communities who are likely to be suitable for a given advertisement. While this approach may be successful in brand building and achieving product awareness, its impact in influencing actual purchase will only be moderate.
With more personalized media available such as a mobile phone with audio and video capabilities, it is now possible to design advertising models which can stream personalized advertisements based on a precise profile analysis of the prospective buyer. These models essentially are those which are based on the principle of buying the attention of the viewer for a price. Some of the prior arts such as the one proposed in U.S. Pat. No. 5,794,210, entitled “Attention Brokerage,” of which A. Nathaniel Goldhaber and Gary Fitts are the inventors, describes a system; in which the consumer is offered with a list of options of advertisements along with accompanying incentives. In the above invention, the focus is confined to the advertising on computer networks and the targeting is based on the demographic profile of the prospective buyer. These profiles are derived from the information voluntarily supplied and by subsequent actions on the Internet by the individuals and are not based on their previous purchase transactions and hence not based on any purchase prediction.
One of the prior art exists in the form of a product by SLP InfoWare wherein the behavior of an existing customer of a particular service is analyzed based on the her transactions such as her enquiry, her debt credit history etc. This product has application in predicting the behavior of customer by analyzing her the online transactions and predicts the possible purchases. However this product address the behavior prediction based on in house transaction data available with a service provider or data on online transaction on the web does not address the transaction data related to the retail purchases made by the customer.
In the model of advertisement where incentive is offered for accepting the targeted advertisement, there is a greater necessity for the advertisement to be relevant to the prospective buyer's profile in general and to his/her immediate purchase requirements in particular. The key issue in such an advertising model is acquiring of an individual profile model for each prospective buyer based on which a relevant advertisement can be selected. The main challenge is in acquiring the data related to the individual's transaction and then extracting a dependable model of his/her behavior and purchase pattern from this data. Some of the prior arts have addressed the selection of advertisements for the targeted buyer using demographic information of the buyers and comparing with that of the previous buyers of the same product. U.S. Pat. No. 5,515,098, entitled “System and method for selectively distributing commercial messages over a communications network,” of which John B. Carles is the inventor, employs this approach in selecting the advertisements for prospective buyers based on the demographic information of the customers who have already bought the product. This invention addresses the question of targeting advertisements to individual or a group of household connected by communication networks and assumes that such a network has a capability to distribute distinct content to individual device terminals. However, the profiles considered are not of individuals but groups such as members of a household.
Another prior art as described in U.S. Pat. No. 6,216,129, entitled “Advertisement selection system supporting discretionary target market characteristics,” of which Eldering; Charles A. are the inventors, describes an advertisement selection system in which vectors describing an actual or hypothetical market for a product is determined. This system uses consumer characterization vector, which is correlated with the advertisement characterization vector to determine the suitability of the advertisement to the consumer, the consumer profile is mainly derived from demographic profile and purchase transactions. Based on this data, a set of Heuristic rules defining a probabilistic measure of demographic characteristics of a person performing the transactions is derived; these rules are used to define the profile of consumer based on her demographic characteristics. This system uses a statistical approach in identifying a consumer suitable for a given advertisement. However, in a scenario where more personalized devices such as third generation mobile phone is available, there is an opportunity for precise targeting of an advertisement based on the individual consumer profile rather than using a statistical correlation of demographic information.
Another aspect of target advertisement is the matching of the presentation aspects of the advertisement. It is a well-appreciated fact that the value of an advertisement solely depends on its ability to attract and retain the attention of a viewer. And therefore, advertisement customized to suit the viewer's specific preferences would be more successful in retaining the viewer's attention. A target advertisement would require a system which would on one hand, learn the preferences of an individual and on the other hand, customize the advertisement to suite the viewer's preferences. This system would be more effective if this learning of the profile and subsequent customization can be automated.
In light of the above, there is a need for a comprehensive system, to account for the following aspects of the target advertisement,    1. The advertisement selection should be based on the characteristics of individual subscribers.    2. The ad selection should be relevant to the purchase prediction made for the individual subscriber.    3. Purchase prediction should be based on the multiple factors, which are likely to influence the purchase such as festivals, sales events, personal events etc.    4. The selected ad should have relevance to the current location of the subscriber.    5. System should be capable of learning subscriber characteristics    6. Customize the advertisement to suit the subscriber's audiovisual preferences.    7. Capability to provide with promotional offers suitable to the individual characteristics of the subscriber.    8. Interactive advertisement streaming which facilitates viewer's interaction with the system.    9. System with overall flexibility in streaming to suit the viewer's convenience and preferences.    10. Use m-commerce to facilitate online transactions related to the advertisements viewed.    11. To provide counseling and information on the products or services desired by the viewer based on advertisements and through the associated call centers.